DiscoverMaterialism: A Materials Science PodcastEpisode 83: Computed Tomography at Zeiss
Episode 83: Computed Tomography at Zeiss

Episode 83: Computed Tomography at Zeiss

Update: 2024-02-27
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Description

Examining the inside of a material is often a destructive process that risks obscuring or deforming critical details. However, advances in computed tomography have opened new opportunities to obtain high resolution, three-dimensional reconstructions of materials in a non-destructive manner. Through this technique materials scientists can now identify cracks and voids in materials without the need for mounting and polishing, observe processes like battery degradation and dendrite growth in real time, and even obtain 3D diffraction data for identifying phase distributions in a material. In covering this fascinating topic, we are joined by William Harris from Zeiss Microscopy who shares his expertise as he walks us through the many ways computed tomography is reshaping materials science.


Selected References:



  • Withers et al. X-ray computed tomography [LINK]

  • Villarraga-Gómez et al. Assessing rechargeable batteries with 3D X-ray microscopy, computed tomography [LINK]

  • Finegan et al. Investigating lithium-ion battery materials during overcharge-induced thermal runaway [LINK]

  • XinChen et al. Interlaminar to intralaminar mode I and II crack bifurcation due to aligned carbon nanotube reinforcement of aerospace-grade advanced composites [LINK]

  • Plessis et al. Effects of defects on mechanical properties in metal additive manufacturing: A review focusing on X-ray tomography insights [LINK]

  • Refuting a 70-Year Approach to Predicting Material Microstructure [LINK]

  • CT Analysis of a Meteorite [LINK]

  • Johnson et al. Analysis of the interdependent relationship between porosity, deformation, and crack growth during compression loading of LPBF AlSi10Mg [LINK]

  • Badran et al. Automated segmentation of computed tomography images of fiber-reinforced composites by deep learning [LINK]

  • Villarraga-Gómez et al. Improving throughput and image quality of high-resolution 3D X-ray microscopes using deep learning reconstruction techniques [LINK]


This episode is sponsored by Zeiss Microscopy. With over 175 years of innovation in microscopy, ZEISS is proud to offer an extensive suite of optical, 3D X-ray, SEM, and FIB-SEM microscopes to help scientists and engineers understand their materials. Every ZEISS microscope comes with the commitment of providing the highest quality instrument, deep application expertise, and a robust global support network. You can learn more about their work and services by visiting their website.


The Materialism Podcast is sponsored by Cal Nano, leading experts in spark plasma sintering and cryomilling technologies. You can learn more about their work and services by visiting their website.


This Materialism Podcast is also sponsored by Materials Today, an Elsevier community dedicated to the creation and sharing of materials science knowledge and experience through their peer-reviewed journals, academic conferences, educational webinars, and more.


Thanks to Kolobyte and Alphabot for letting us use their music in the show!


If you have questions or feedback please send us emails at materialism.podcast@gmail.com or connect with us on social media: Instagram, Twitter.


Materialism Team: Taylor Sparks (co-host, co-creator), Andrew Falkowski (co-host, co-creator), Jared Duffy (production, marketing, and editing).


Keywords: Xray Tomography Computed Zeiss CT Materials Research Microstructure

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Episode 83: Computed Tomography at Zeiss

Episode 83: Computed Tomography at Zeiss